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# Lead Data Engineer, Investment Data Platform

- **Company:** Castleton, Town of Inc
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Computing Platforms, Automation of Tests, Microsoft Azure, Code Review, Continuous Integration, Information Engineering, Data Infrastructure, Cursor, Python (Programming Language), Reference Data, Power BI, Azure DevOps Pipelines, Microsoft Copilot, Software Engineering, SQL Databases, Azure Data Factory, Claude Code, Snowflake, Build Management, Data Management, Azure Synapse Analytics, Software Version Control, Databricks
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25303_7fff37090da94353aabf3fd466017440

## About the Role

* 8+ years of hands-on experience in data engineering, analytics engineering, or software engineering focused on data platforms.
 * 3+ years leading technical work, as a tech lead, principal or staff engineer, or engineering manager who still builds.
 * Expert SQL and Python, and deep data modeling and architecture judgment that goes beyond any single tool.
 * Production experience with modern warehouse and lakehouse platforms (Snowflake, Databricks, or similar), dbt, and orchestration tools (Dagster, Airflow, or similar).
 * Strong software engineering practice: version control, code review, automated testing, and CI/CD applied to data.
 * Track record of shipping and operating systems you built, described in terms of what you delivered.

Strongly Valued

 * Experience with investment management systems and data: security master, IBOR/ABOR, OMS, risk, performance, fund accounting, or client reporting.
 * Private markets data, including entity mapping across sources without universal identifiers.
 * Azure data services (Azure Data Factory, Azure DevOps pipelines, Synapse) and Power BI.
 * Experience in asset allocators, asset managers, hedge funds, private markets firms, or financial data providers., * Craftsman mindset: you care about the parts of the system nobody sees.
 * High standards for yourself and the people around you, delivered constructively.
 * Ownership: you see problems through to resolution without being asked.
 * Clear communicator with both engineers and investment professionals.

## Description

* Platform architecture: Design and build the warehouse and lakehouse, data models, orchestration, and semantic layers that the investment organization runs on.
 * Hands-on delivery: Build production-grade Python, SQL, dbt, and orchestration work yourself, including batch and near-real-time pipelines.
 * Engineering standards: Bring software engineering discipline to data: code review, testing, CI/CD, documentation, observability, and data quality controls.
 * Technical leadership: Lead and mentor engineers through design reviews and pairing, set the technical direction for your area, and own outcomes end to end.
 * Business partnership: Work with investment, operations, finance, and reporting stakeholders to turn their needs into durable data products.
 * AI-enabled engineering: Use tools such as Claude Code, Codex, Cursor, and Copilot to move faster without compromising quality or controls., * Architect and build core investment data domains such as security and entity reference data, positions and transactions, performance, risk, and private-markets fund data.
 * Design data models that are correct, reconcilable, and point-in-time aware, with tests and controls that catch problems before users do.
 * Own reliability, performance, and cost of the platform, including monitoring, alerting, and incident follow-through.
 * Review others' work closely, send it back when it isn't right, and make the next version better.
 * Evaluate tooling and vendors across Snowflake, dbt, Dagster/Airflow, and Azure, and make pragmatic build-versus-buy calls.